Serverless on AWS

Developing Serverless applications on AWS with beSharp Cloud Experts

Developing Serverless applications on AWS with beSharp Cloud Experts

The serverless paradigm allows you to build and run scalable applications able to autonomously adapt resources to face request spikes. This will enable you to reduce the effort required to manage the Cloud infrastructure at the basis of their operation. The Serverless development model is flexible and can meet the needs of an infinite series of use cases: these are just some of the most common applications for Serverless solutions on AWS.

Backend for scalable web applications

In multi-tier web architectures that provide high scalability, the serverless model guarantees an improvement both in terms of performance and cost-effectiveness. In addition, managing Serverless applications on AWS is extremely efficient as it doesn’t require any management tasks for infrastructure, operating system, and runtime environment. For example, using Amazon API Gateway, it is possible to create client / server connections that allow calls to be routed to AWS Lambda, the AWS Function-as-a-Service service able to carry out all requests independently. Both Amazon API Gateway and AWS Lambda, like all AWS services for serverless development, are able to scale independently, ensuring ultra-granular cost control and the correct provisioning of resources in any traffic condition. In such a context, databases play a crucial role, too. Amazon DynamoDB is the perfect choice for perfectly supporting workloads in a fast and performing way.

Event-driven applications and Microservices

The peculiar characteristics of Serverless development aid the adoption of microservices and event-driven architectures. By developing Serverless, any event on any application, service, or database may act as a trigger to activate AWS Lambda functions, or Amazon ECS tasks. For example, uploads to an S3 bucket, messages published into an SNS topic or an API call may execute a Lambda function, or they may be delivered to an Amazon ECS service. Using DynamoDB Streams, events occurring at the database level can be used as a trigger for event-driven workloads, too. All this, allows developers to automate entire stacks of configurations or jobs to be performed. 

Serverless SaaS architectures

Developing your SaaS application taking advantage of Serverless paradigm adds even more agility and modularity to your Cloud architecture, and frees you from recurring manual tasks. Taking advantage of Lambda Functions make it is easy to obtain an automatic scaling model capable of autonomously adapting the capacity of resources to the unpredictable traffic that is typical of SaaS applications. Amazon Web Services offers a complete set of services and tools dedicated to Serverless development, thanks to which you can delegate to AWS the provisioning and scaling of resources, the maintenance and updating of operating systems, and several other management activities. beSharp has dozens of Serverless projects realized on Amazon Web Services: some of our most successful cases have been the key to AWS’s recognition of DevOps Competency and, among the few partners in the world, the Competency for the design and the creation of SaaS applications. Thanks to our experience in creating Serverless applications on AWS, we can place at your disposal a team of Cloud Experts able to support your developers, or take charge of all development activities, from design to deployment, to quickly create applications Serverless on AWS in line with AWS Well-architected Framework best practices.

By developing Serverless with beSharp you will get:

  • Serverless design and development following AWS best practices;      
  • Advanced event-driven architectures leveraging producer-consumer models based on Amazon Simple Queue Service (SQS) AWS Lambda, AWS Fargate, and Amazon ECS.     
  • Analysis of your legacy applications and elaboration of a re-engineering strategy that foresees the adoption of scalable, flexible and resilient architectures thanks to the microservices paradigm;      
  • Reduction of prototyping and R&D costs;      
  • Reduction of Time-To-Market.   
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